Probing the Apple M1's Hidden Depths
By Don Scansen, EETimes (December 12, 2020)
Apple’s announcement of the M1 certainly generated some rumblings, but they were insufficient warning of the shockwaves to come. Only after products appeared in the wild and were finally subjected to benchmark testing could the M1 be fully appreciated. The first product from Apple’s chip design team meant for the personal computer line surpassed many competing microprocessors and nearly everything currently in other Apple products, particularly in single core and GPU tests.
Apple was gracious enough to release a die photo (another little detail that put them into the company of AMD and Intel since that is now a traditional new process announcement strategy) and these were quickly annotated by processor uber geeks like Andrei Frumusanu at Anandtech.
We know from the earliest announcements that the ARM-powered M1 would be solidly in the system-on-chip category. For the chiplet designs that are expected to continue to take over traditional CPU designs, analysts may have an easier time identifying functional elements since they will be physically distinct pieces of silicon. Understanding the architecture of an SoC takes a little (maybe a lot) more squinting.
E-mail This Article | Printer-Friendly Page |
Related News
- Apple, AMD Back TSMC's Tripled Investment, Tech Upgrade in Arizona
- intoPIX unveils new FastTicoRAW & FastTicoXS codecs for Apple silicon and makes the switch to ARM-based technology simple
- Apple M1 Processor, Passing on the Chiplets
- Apple to Buy Intel's Modem Business for $1 Billion
- Is Apple planning to acquire Intel's mobile business?
Breaking News
- Jury is out in the Arm vs Qualcomm trial
- Ceva Seeks To Exploit Synergies in Portfolio with Nano NPU
- Synopsys Responds to U.K. Competition and Markets Authority's Phase 1 Announcement Regarding Ansys Acquisition
- Alphawave Semi Scales UCIe™ to 64 Gbps Enabling >20 Tbps/mm Bandwidth Density for Die-to-Die Chiplet Connectivity
- RaiderChip Hardware NPU adds Falcon-3 LLM to its supported AI models